What Is Latent Semantic Indexing (LSI) | Reflect Digital

Latent Semantic Indexing

Latent semantic indexing helps search engines to better understand context of a webpage's content.


Latent Semantic Indexing LSI, Latent Semantic Analysis

What is Latent Semantic Indexing (LSI)?

LSI, sometimes referred to as latent semantic analysis, helps search engines to understand the context behind the content as well as the searcher’s intent. This enables search engines to identify related keywords and provide more relevant results to the user.

For example, having a primary keyword for content about Apple, you’ll want to use related keywords that relate to your primary keyword. Phrases like ‘iPhone’ and ‘Steve Jobs’ reinforce that your content is about the technology company and not the fruit.

LSI was first developed as a mathematical methodology in the 1980s to improve information retrieval from documents. It focuses on understanding not just words themselves, but the relationships between words to better understand content.

In the early days of search engines, they had greater difficulty with identifying synonyms, related words and understanding the intent and context of a user’s search. Developments related to LSI have been incorporated into search engines over time to better understand the intent of users, and identify the content that should be returned for a query.

How does LSI help Search Engine Optimisation (SEO)?

It is unclear the extent to which LSI is used in search engine algorithms. Google has evolved beyond LSI towards more sophisticated means of understanding content. Nonetheless, LSI gives businesses an idea of how to better optimise their site and follow good SEO practices.

In theory, using synonyms and related terms is likely to help search engines understand your content. This may lead to increased visibility for more relevant searches.

However, there’s no significant evidence that LSI is specifically used as part of search engine algorithms. The principles of LSI can still help you write more relevant content, and give your users the context to better understand your content.

The integration of LSI principles will likely become deeper with the prevalence of devices reliant on voice search. This includes Google Assistant, Amazon Alexa, Apple’s Siri and Microsoft’s Cortana.

These devices are required to understand the semantic nature of spoken language in order to return the most relevant results to the user. Along with understanding the context and intent of a query, they must understand the unique vocal characteristics of individual users in order to meet their needs.

As a result, it is important businesses, SEOs and marketers more generally are aware of the importance of LSI in order to improve the long-term visibility of their content.

How can you find LSI Keywords?

Finding LSI keywords involves keyword research and analysis. Doing so will ultimately lead you to words you may not have considered including in your content, and maybe even primary keywords you wish to optimise new pages for.

Using a variety of keyword tools, along with manual investigation of related searches and suggestions, can help you identify and expand the keywords to include in your content. Looking at what your competitors are doing can also help you enrich your content for users.

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